Scientific and Statistical Database Management, International Conference on (2007)
Banff, Alberta, Canada
July 9, 2007 to July 11, 2007
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/SSDBM.2007.8
Ruslan Fomkin , Uppsala University, Sweden
Tore Risch , Uppsala University, Sweden
High energy physics scientists analyze large amounts of data looking for interesting events when particles collide. These analyses are easily expressed using complex queries that filter events. We developed a cost model for aggregation operators and other functions used in such queries and show that it substantially improves performance. However, the query optimizer still produces suboptimal plans because of estimate errors. Furthermore, the optimization is very slow because of the large query size. We improved the optimization by a profiled grouping strategy where the scientific query is first automatically fragmented into subqueries based on application knowledge. Each fragment is then independently profiled on a sample of events to measure real execution cost and cardinality. An optimized fragmented query is shown to execute faster than a query optimized with the cost model alone. Furthermore, the total optimization time, including fragmentation and profiling, is substantially improved.
Ruslan Fomkin, Tore Risch, "Cost-based Optimization of Complex Scientific Queries", Scientific and Statistical Database Management, International Conference on, vol. 00, no. , pp. 1, 2007, doi:10.1109/SSDBM.2007.8